1. Technical Field
One or more embodiments of the present invention generally relate to operating point management. In particular, certain embodiments relate to managing operating points in multi-core processing architectures.
2. Discussion
The popularity of computing systems continues to grow and the demand for more complex processing architectures has experienced historical escalations. For example, multi-core processors are becoming more prevalent in the computing industry and are likely to be used in servers, desktop personal computers (PCs), notebook PCs, personal digital assistants (PDAs), wireless “smart” phones, and so on. As the number of processor cores in a system increases, the potential maximum power also increases. Increased power consumption translates into more heat, which poses a number of difficulties for computer designers and manufacturers. For example, device speed and long term reliability can deteriorate as temperature increases. If temperatures reach critically high levels, the heat can cause malfunction, degradations in lifetime or even permanent damage to parts.
While a number of cooling solutions have been developed, a gap continues to grow between the potential heat and the cooling capabilities of modern computing systems. In an effort to narrow this gap, some approaches to power management in computer processors involve the use of one or more on-die temperature sensors in conjunction with a power reduction mechanism. The power reduction mechanism is typically turned on and off (e.g., “throttled”) according to the corresponding temperature sensor's state in order to reduce power consumption. Other approaches involve alternatively switching between low and high frequency/voltage operating points.
While these solutions have been acceptable under certain circumstances, there remains considerable room for improvement. For example, these solutions tend to make the system performance more difficult to determine (i.e., the solutions tend to be “non-deterministic”). In fact, temperature based throttling is often highly dependent upon ambient conditions, which can lower the level of performance predictability. For example, on a warm day, more throttling (and therefore lower performance) is likely to occur than on a cool day for the same usage model. In addition, reducing power by throttling between operating points can add to the inconsistency of the user's experience. These drawbacks may be magnified when the gap between the dissipated power and the external cooling capabilities increases due to the presence of multiple processor cores in the system.